NishMath

Probability and statistical methods are being explored across various fields, including applications of probability distributions with examples from finance and error analysis. The focus includes an examination of counting techniques in probability and the study of joint, marginal, and conditional probabilities. This research also delves into the transformation of distributions, all of which are crucial for real-world applications.

This area of study uses mathematical and computational methods like Monte Carlo simulations to estimate probabilities. The work also explores how data analysis has evolved from traditional statistical methods to AI-driven insights, along with the fundamentals of linear regression, which serves as a key tool in data analysis. Furthermore, the work considers methods for hypothesis testing such as one-sample, two-sample, and paired t-tests using real world examples. Another area being examined is descriptive measures of association, and data management techniques such as SQL server statistics. A specific challenge was also examined, that of finding integer tetrahedrons with a given volume.

ImgSrc: miro.medium.com

References:

• www.analyticsvidhya.com - What are Joint, Marginal, and Conditional Probability? - 12d
• gsapra.medium.com - Unveiling the Power of Probability: A Deep Dive into Key Concepts and Applications - 8d

Classification:

• HashTags: Probability Statistics DataAnalysis
• Target: Prediction
• Product: Statistics
• Feature: StatisticalAnalysis
• Type: Research
• Severity: Medium